Knowledge management, in a typical business organization, is needed for achieving organization's primary objectives of improved business performance and to attain a competitive edge over others by adopting knowledge management as a strategic asset for gaining insights and experiences. In general, the process of knowledge management and acquisition demands a research level understanding of the subject domain such that the documents retrieved using search engines is digitally read and comprehensively analyzed. However, this does not imply that a researcher is all time capable of coming up with a most optimum solution to a given query, for he may have overlooked some of the other associated important aspects that were desirable to consider or he may not be able to capture the events that gets dynamically associated with any subject which may be valuable to contribute towards the attainment of optimal solution.
In some applications, Question Answering (QA) systems do use knowledge base in the form of ontologies to retrieve the most relevant document or information pertaining to the query. Ontology is a way to represent knowledge within a specific domain. This system is well documented in the existing prior arts. For example, Aqua-Log is a QA system which takes queries expressed in natural language and ontology as input and returns answers drawn from the available semantic markup. Other existing prior art discusses building an ontology for agriculture domain specifically. However the ontology used in the above arts are fixed, irrespective of external stimuli. This approach often leads to a “general” answer and not “specific to the question” answer. This is because QA systems are developed for certain domain and are anticipated to answer queries related to specific domain and not to specific person who is asking the query. None of the existing literature discusses the representation of knowledge such that it configures itself based on the external stimuli in order to answer the query specifically and satisfactorily.
For personalized response one should have access to a system that enables them to see a relationship between the domain knowledge and the external stimuli. Currently there is no systematic way of retrieving distilled knowledge from vast repositories of knowledge available over the internet. In the light of foregoing there is a need in the art for a knowledge management system that is easy to navigate and is capable of configuring itself in response to the query issued by the user along with the external stimuli in order to provide a solution/knowledge that best matches the user inquisition.